Why Computers Can't Make It as Stand-Up Comics

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Computers may have beaten us in chess and "Jeopardy!" — but can
they create and tell a good joke?

Fortunately for comedians like Jon Stewart, who verbally sparred
with a right-wing doppleganger of
"Jeopardy!"-winning computer Watson on his show this week,
any computer cracking wise is likely to need human writers for
the foreseeable future.

A new review of the literature on the development of the human
mind indirectly suggests how far computers have to go before they
can present themselves as our new comedic overlords.

The article, coming out in the journal Science this week, focuses
on how the
human mind, despite the messy and inconsistent information it
receives from the world, gets to be so high-functioning.

"Most machine learning is about learning from very massive
datasets. Human intelligence is also about coming to a pattern
about how things work," said Josh Tenenbaum, an MIT professor who
is one of the paper’s four co-authors.

And unexpected patterns of words and concepts are the essence of
comedy.

The human mind, Tenenbaum told LiveScience, seeks to structure
objects in a logical way to help understand them. One example is
the political spectrum in the United States, which is commonly
represented as a simple left-to-right line and, Tenenbaum said,
may need to be expanded to a second dimension for a fuller
understanding of ideas.

"Our language shows there is an underlying one-dimensional space
to how we think about politics," said Tenenbaum, a professor of
computational cognitive science.

This ability to structure information, it seems, is present to
some degree at birth.

"As a matter of empirical fact, we know
newborns who see object s for the first time ... already are
able to represent objects the first time they encounter them,"
said Elizabeth Spelke, a professor of cognitive psychology at
Harvard, who was not involved in the review article.

"I see this paper as laying out a blueprint for a future program
of research," Spelke added. The next step, she said, is to see
whether the models can predict how we know what we know.
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Humanlike machines

Part of the success of the human mind is that it is able to
assimilate facts into a structure while simultaneously evaluating
their "truth" based on previous knowledge. To figure out how it
does that, the researchers say, we must answer two questions: how
the mind interprets numbers, and how it interprets symbols and
facts.

"You have to have both of these things, and you have to
understand how they go together," said Tenenbaum. "We have to
understand how they work together to understand
how the mind works."

That understanding could enable development of a computer with
similar capabilities. "The road is ridden with obstacles but the
goal is clear: to make a machine act intelligently in various
areas," said Judea Pearl, a professor of computer science at
UCLA, who was not involved in the study.

Computers, Pearl said, are able to understand statistics and
actions. But they cannot handle the next level — understanding
alternative possibilities.

For instance, he said, the sense of regret is based on the idea
that our minds can evaluate what would have happened had we done
something differently — a thought level that computers have not
yet reached.

Tenenbaum used Google as an example. The search engine rapidly
looks for word patterns rather than actually understanding what
the user is asking. Tenenbaum described its inner workings as
"fast and stupid."

While humans are able to consider alternatives, one challenge has
always been in explaining why some humans are bad at
understanding cause and effect.

For instance, why are some medical treatments so popular when
they have no scientific basis? Homeopathy — the use of extremely
diluted symptom-causing substances to treat patients with certain
ailments — is used by 4.8 million Americans annually despite the
fact that "a number of its key concepts are not consistent with
established laws of science," and "most analyses of the research
on homeopathy have concluded that there is
little evidence to support homeopathy as an effective
treatment for any specific condition, and that many of the
studies have been flawed," according to the National Center for
Complementary and Alternative Medicine.

The Science review touches on those ideas, explaining how human
knowledge is constructed on what is called a Bayesian system,
meaning the mind gives new ideas a probability of being true
before investigating them. This can account for why the mind can
assemble rational thoughts — and why once an irrational thought
is accepted, it can be hard to change, as new facts that
contradict it are given a low probability of truthfulness.

One future direction in the human aspects of mind research is
explaining how to fix our own bugs.

"I think it's really interesting why we seem smart and rational
in one domain, and shift ... and people can seem really
irrational," said Spelke. "If one is going to come up with an
adequate account of the human mind, one would have to answer
this."

In designing the computer mind, it may be important to understand
how to avoid those irrational
flaws in the human one.

But even when computers pass that stage, they still won't
understand the conventions of human language necessary to subvert
them and construct a joke. And those conventions are critical for
any creative work.

So take heart: Watson may beat Ken Jennings, Brad Rutter or you
at "Jeopardy!" but, as Tenenbaum noted, you would beat him easily
at writing the questions.